With the advent of the Internet the transmission of audio and video content, in a linear or non-linear mode (e.g. VOD, catch-up, etc . . . ), has undergone enormous expansion and the dissemination of terminals that can receive audiovisual signals (smartphones, tablets, PCs, connected devices, etc . . . ) has likewise increased. Unfortunately, there exists no common standard for serving all the devices connected to the network (each of which with a different screen and resolution). For this reason it is necessary to prepare the content with different formats (for example Smoothstreaming, http Live Streaming, Mpeg DASH, . . . ) and for each format, in order to guarantee the end customer the maximum user experience, different compression profiles (bit rates) have to be prepared in order to be able to deliver content from the Internet to the end customer in conformity with the latter's connection bandwidth.
Therefore, for any one item of content, or audiovisual channel, for example, 8 levels of compression must be generated: from the one defined “audio-only” (e.g. 32 or 64 Kbps) or “level 8”, to the “HD” high resolution format (e.g. 3 or 4 Mbps) or “level 1”; each of the levels must often be rendered in at least 2 or 3 formats, which can result in a total of 24 copies of the same content and/or channel with different features.
In order to ensure maximum quality and efficiency, the compression is performed starting from the original signal or content to which the quality of production corresponds (for example, HD with video quality requiring a bandwidth even greater than 50-100 Mbps, up to 10 Gbps for live content).
Maximum efficiency means having the best quality at the lowest possible bit rate. In fact, for the content provider, as well as for the global network, each bit saved implies savings of transmission resources and thus a better overall use of resources.
Therefore, being able to compress audiovisual content in the best possible way by containing the bit rates for each level while ensuring the highest possible quality represents a technical challenge for distribution over the Internet.
Once these numerous copies of the same content/channel have been created, the content/channel has to be transmitted over the Internet 24 times (since each customer can have a different connectivity at any given time). Therefore, the transmission resources necessary (and hence the costs) are n times greater than if a single content item/channel were to be sent over the Internet. In the case of VOD, it follows that the required storage capacity is also n times greater.
If a Content Delivery Network (CDN) is used for distribution to end customers, the situation does not change: in this case, as well, 24 copies of the content/channel must be managed.
Obviously, this system is scarcely efficient for distribution, but it is the best insofar as video quality is concerned, since “lossy” compression, be it MPEG 2, AVC, HEVC or any other format, will be better the higher the quality of the source is.
Recently, numerous solutions have been made available (for example by Amazon and Verizon) which involve compressing content directly over the Internet (via cloud computing), avoiding the need for the service provider (media company) to manage a complex compression chain; however, such solutions entail sending content over the network in a scarcely efficient manner and usually involve a complete outsourcing of transcoding services to the cloud provider, taking away all control from the media company.
In detail, such solutions require the content provider (or media company) to send a single content item/channel and then compression into the different formats and bit rate levels takes place over the network (or over the CDN, prior to distribution to the end customer or prior to storage of non-linear content such as VOD). These solutions are conceived to set the compression systems at a common factor and lower the costs of the content provider by using encoders shared with different content providers, thus reducing their number, reducing backup and operational maintenance and improving the working speed/performance by being able always to exploit compression resources 100%. However, these solutions still present some disadvantages from a technical viewpoint. The most evident of these disadvantages is that the upload of the content/channel to the Internet occurs at a high bit rate, e.g. 50-100 Mbps or more (up to 3 Gbps or 10 Gbps for live broadcasts), as mentioned above.
The solution is thus not efficient since it requires large transmission resources (and thus implies high costs) and does not allow the media company to have any control over the distribution chain. One solution to this drawback consists in sending “pre-compressed” (mezzanine) content to the network, together with information generated by the media company on how to manage the subsequent steps of compression in the cloud, thereby optimizing the integration between the compression systems of the media company and those made available by the cloud provider. Even if pre-compressed to 10 Mbps (i.e. to a level that is not too low), such content generally loses a great deal of information (compared to the 50-100 Mbps of a video source with HD quality); therefore, the subsequent multiformat/bit rate compression operation will be less efficient and of lower quality (even at the same bit rate) than that performed starting from content or channels with HD production quality.
Therefore, the lower efficiency means that in this latter case, in order to have the same quality for each video level, a bit rate that is 10-20% higher may be needed in order to have the same result as a transcoding that starts from a high quality source (for example, the highest level in the compression and transcoding option will be 5 Mbps when starting from a 10 Mbps source, whereas when starting from a high quality source at 50 Mbps, it will be possible to arrive at 4 Mbps without compromising quality, and so on for lower levels). Moreover, a transcoding system not completely outsourced to the cloud and including a pre-compression step in the production centre of the media company, in addition to reducing the costs of transmitting the pre-compressed content, benefits from the generation of encoding information at the level of the media company in an accurate manner such as only processing in the media company's production centre can guarantee.
None of the known systems, moreover, envisages the advantages deriving from a management of the transcoding system which includes a pre-compression step managed by the production centre of the media company combined with the generation of further levels of encoding by a virtualized distribution centre, such as a Content Delivery Network, while at the same time enabling high levels of encoding quality to be reached at the various levels to be generated.